Publication date
January 2024
DOIAbstract
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-LSTM, and (k) SSC.</p
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-LSTM, and (k) SSC.</p
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>Classification errors (1-AUC) for classifiers trained for one class against another class. All pa...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-L...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>(UA, user’s accuracy; PA, producer’s accuracy; OA, overall accuracy; Kappa, Kappa statistics; UNC...
<p>These are NB (A) and SVM-R (B). The color code indicates average accuracy per composition (the hi...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
<p>The classification precision and recall values are shown for each class in all the tables. The ce...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual ...
Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of De...
Confusion matrix (error matrix): the entry in row k and column l is the number of test datapoints wh...
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>Classification errors (1-AUC) for classifiers trained for one class against another class. All pa...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
(a) RF, (b) GBM, (c) AdaBoost, (d) LR, (e) SVC, (f) SVEC-H, (g) SVEC-S, (h) CNN, (i) LSTM, (j) CNN-L...
<p>Confusion matrix for the classifiers of RF, SVM, and WKNN using the input dataset with all the pr...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>(UA, user’s accuracy; PA, producer’s accuracy; OA, overall accuracy; Kappa, Kappa statistics; UNC...
<p>These are NB (A) and SVM-R (B). The color code indicates average accuracy per composition (the hi...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
<p>The classification precision and recall values are shown for each class in all the tables. The ce...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
<p>The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual ...
Confusion matrix for the classification of the 724 real hESC images using the CNN architecture of De...
Confusion matrix (error matrix): the entry in row k and column l is the number of test datapoints wh...
<p>Confusion matrix for classification by the statistical models versus the empirical models.</p
<p>Classification errors (1-AUC) for classifiers trained for one class against another class. All pa...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
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